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Occlusion gesture recognition based on improved SSD

Research output: Contribution to journalArticlepeer-review

  • Shangchuan Liao
  • Gongfa Li
  • Hao Wu
  • Du Jiang
  • Ying Liu
  • Juntong Yun
  • Yibo Liu
  • Dr Dalin Zhou
Gesture recognition has always been a research hotspot in the field of human‐computer interaction. Its purpose is to realize the natural interaction with the machine by recognizing the semantics expressed by gesture. In the process of gesture recognition, the occlusion of gesture is an inevitable problem. In the process of gesture recognition, some or even all of the gesture features will be lost due to the occlusion of the gesture, resulting in the wrong recognition or even unrecognizability of the gesture. Therefore, it is of great significance to study gesture recognition under occlusion. The single shot multibox detector (SSD) algorithm is analyzed, and the front‐end network is compared. Mobilenets is selected as the front‐end network, and the Mobilenets‐SSD network is improved. In tensorflow environment, based on the improved network model, the self‐occlusion gesture and object occluding gesture are trained in color map, depth map, and color and depth fusion respectively. The recognition models of self‐occlusion gestures and object‐occlusion gestures in color map, depth map, and color and depth fusion are obtained. And compare and analyze the learning rate, loss function, and average accuracy of various models obtained for occlusion gesture recognition.
Original languageEnglish
JournalConcurrency and Computation: Practice and Experience
Early online date19 Oct 2020
Publication statusEarly online - 19 Oct 2020


  • Occlusion Gesture Recognition Based on Improved SSD

    Rights statement: This is the pre-peer reviewed version of the following article: Liao, S, Li, G, Wu, H, et al. Occlusion gesture recognition based on improved SSD. Concurrency Computat Pract Exper. 2020; e6063. Ahead of print, which has been published in final form at This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.

    Accepted author manuscript (Post-print), 2.73 MB, PDF document

    Due to publisher’s copyright restrictions, this document is not freely available to download from this website until: 19/10/21

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